Optical Laser Systems and Methods for Determining Contamination

The following relates generally to contaminate determination, and more particularly to optical laser system and methods for determining contamination.

The need to determine the amount of contaminant (such as dust) that might either penetrate or accumulate on the functional components of a variety of equipment types is common, particularly during testing or validation of that equipment. In many of these situations, the space where the measuring equipment may be placed is constrained. Also, the target component may have an angular or translational movement adding to system difficulty. For example, where a deposition surface is stationary, a scanning process may be much simpler because time may not be important, so a laser head can move over the inspecting area and sample images without considering the time factor. However, where there is relative movement between the accumulation surface (e.g., a tray) and the position of the laser sensor, the system will consider timing and corelate the acquired images with the position of the moving deposition surface. In addition, acquisition time becomes important as the sample time must be sufficiently small to avoid registering moving images.

Existing optical systems may be based on digital imaging processing that have expensive, larger footprints and sensitive camera type equipment. It may be desirable to have a device that is robust while still providing accurate image acquisitions and that may also be inexpensive. Besides the significant cost of such equipment, the typical optical camera does not allow for lenses focusing on reduced distances (i.e., “close in” measurements). As a result, such systems are too large for placement in confined cavities. Moreover, such systems are prone to be damaged by the same contaminant materials they are intending to measure, and by vibrations or high accelerations all of which effectively limit the applicable cases.

Accordingly, there is a need for an improved system and method for contaminant measurement that overcomes at least some of the disadvantages of existing systems and methods.

Provided is a system for contaminant determination. The system includes a laser sensor for sensing contaminant on an object to generate an image, and a sensor interface and image processing module that receives an image of laser light that is sensed on the object. The sensor interface and image processing module processes the image using image characterization and image processing to provide contaminant determination.

The laser sensor is configured for close proximity measurement of the amount of contaminant in a focal point of the optical sensor.

The system may be used to estimate a degree of change in contaminant level from an initial condition.

The system may be used to measure exact amounts of contaminant collected.

The system may further include an exposure subsystem that performs two exposures for each frame to achieve ambiental and infrared (IR) parasitic rejection.

The system may further include an image stitching module that stitches individual frames into a complete picture to provide a detailed image analysis investigation.

The object may include a rotary joint having a confined space where presence of contaminant is determined.

The system may further include a rotation actuation controller for controlling the rotation of the object, and a laser actuation controller for controlling actuation of the laser sensor.

The system may further include a real time clock that implements a time base for a sequence of repeated frames acquisition.

The contaminant may include any one or more of dust, debris, and lunar regolith.

The laser sensor may determine if the object is moving improperly by monitoring contaminant on a surface of an object through collected images.

Provided is a method for contaminate determination. The method includes receiving an image having scanned frames, wherein the scanned frames have a plurality of image pixels, convoluting operators with the scanned frames, evaluating the size of the identified grain particle within the perimeter of the scan, and combining, at the plurality image pixels, a gradient approximation resulting in a magnitude and a direction of the gradient.

The method may further include performing a spectral histogram.

The method may further include performing an integrator.

The method may further include performing an accumulation.

The method may further include dithering the image.

The method may further include preparing the subsequent edge detection by morphing the dark and light dots in a connected network.

The method may further include a differential operator application that confines the image pixels that could falsely result from transitions of light to black.

The method may further include performing actual edge detection with a Sobel-Friedman operator.

The method may further include normalization of groups of dark and white image pixels to provide boundary identification.

The method may further include a calibration phase that detects functional parameters that are dependent on a system.

Other aspects and features will become apparent, to those ordinarily skilled in the art, upon review of the following description of some exemplary embodiments.

Various apparatuses or processes will be described below to provide an example of each claimed embodiment. No embodiment described below limits any claimed embodiment and any claimed embodiment may cover processes or apparatuses that differ from those described below. The claimed embodiments are not limited to apparatuses or processes having all of the features of any one apparatus or process described below or to features common to multiple or all of the apparatuses described below.

One or more systems described herein may be implemented in computer programs executing on programmable computers, or dedicated signal processing controllers (e.g., dsPIC processor), each comprising at least one processor, a data storage system (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device.

The dsPIC (digital processor peripheral interface controller) is a type of microcontroller that has additional hardware components that allows the processor to process input data on hardware rather than software control. The dsPIC may include a multiplication barrel which is a type of hardware stack that performs the multiplication operation as a sequential addition to the stack. The dsPIC has a controller having a fast clock which may result in reduced time execution which may be advantageous for image processing.

Each program is preferably implemented in a high-level procedural or object-oriented programming and/or scripting language to communicate with a computer system. However, the programs can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Each such computer program is preferably stored on a storage media or a device readable by a general or special purpose programmable computer for configuring and operating the computer when the storage media or device is read by the computer to perform the procedures described herein.

Further, although process steps, method steps, algorithms or the like may be described (in the disclosure and/or in the claims) in a sequential order, such processes, methods and algorithms may be configured to work in alternate orders. In other words, any sequence or order of steps that may be described does not necessarily indicate a requirement that the steps be performed in that order. The steps of processes described herein may be performed in any order that is practical. Further, some steps may be performed simultaneously.

A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the present invention.

The present disclosure provides systems and methods for contaminant determination. Contaminant determination may include, for example, estimating a degree of change in contaminant level from an initial condition (e.g., identifying the presence of contaminant, and its degree of change over time) or measuring exact amounts of contaminant collected.

1 FIG. 100 100 102 104 100 102 104 102 102 102 Referring to, shown therein is a block diagram of a systemfor determining or measuring contaminant, according to an embodiment. The systemdetermines if contaminantis on a surface of an object. The systemmay measure the amount of contaminanton the object. The contaminantrefers collectively to the individual contaminant particlesor may be referred to as contaminant simulant particles.

102 102 104 100 104 100 102 The contaminantmay be particles including any one or more of dust, debris, lunar regolith, or other contaminants. The contaminantmay be any material that may damage the objector other equipment. The measurements of the contaminant measurement systembeneficially facilitates disposing or protecting the objectagainst damage. The systemtesting in the presence of contaminantparticles may be accomplished using analogue or simulant contaminant particles.

104 104 100 102 The objectmay have a confined space. The confined space may be a space where typical camera imager and/or sensing equipment does not fit due to equipment size and focal length requirements. The confined space may be just large enough for an optical laser to get size information. The objectmay be a rotary joint. The systemmay estimate if contaminantis coming through a seal of the rotary joint, while the rotary joint is in motion. The rotary joint may be on a robot. The robot may be a space robot. The robot may be a lunar robot operating in a lunar environment.

102 104 100 The to be measured contaminantmay be suspended in an environment around the object(i.e. floating, drifting, or airborne). The environment may be in a vacuum such as space. The environment may be a typically fluidic atmosphere through which contaminant measurement systemis traveling.

104 104 The objectmay be a moving or stationary target. For example, the objectmay be moving with speeds that exceed 40 inches/second and accelerations of up to 50 g.

100 106 102 106 102 106 104 106 106 104 106 104 The systemincludes a laser sensorfor sensing the contaminant. The laser sensormay be an optical laser sensor that optically measures the contaminant. The laser sensormay include an infrared sensor that projects infrared laser light from a source of light (e.g., infrared emitter such as a light emitting diode (LED)) onto the object. The laser sensorincludes a read head (e.g., an area on the sensordiode that is sensitive to light (e.g., in the nano meter wavelength)) that receives the infrared laser light reflected back from the object. The laser sensormay not be influenced by light external to the object.

106 2 102 106 106 106 100 The laser sensormay include a classlaser sensor configured for close proximity measurement of the amount of contaminantin a focal point of the optical sensor. The laser sensormay operate in the spectrum 940-950 nm. Depending on the selection of the laser sensor, accurate measurements that exceed 16,000-25,000 DPI may be achieved on a 2.3-2.6 square millimeter target. The systemmay provide up to 14,000 frames per second (FPS) without resorting to special direct memory access techniques.

100 102 100 106 106 106 The systemmay provide a positive indication of contaminant. The systemmay provide a qualitative assessment of the magnitude of the contaminant present. Where the substrate is fully covered with contaminants, the optical comparison may not be able to determine anything more than ‘100% area coverage’. The laser sensormay have a response curve throughout the functional range of the laser sensor. The laser sensormay have a “cut-off” range.

106 104 104 In an optional embodiment, the laser sensormay determine if the objectis moving improperly (wobbling) by monitoring an image (e.g., dot) on the object.

100 100 The systemmay be used to evaluate contaminant deposition. The systemmay be used in any one or more of other applications including positional control of machine components in relative movement, vibration monitoring of the same type of components, real time lubrication failure in moving interfaces.

100 In particular, the systemmay provide position control to ensure that a certain component comes in the desired position at the precise moment in time (e.g., reciprocating mechanisms, valve position control).

100 The systemmay provide pattern recognition such as false coin identification by exploring the surface of the coin and comparing it with a reference reflection signature.

100 100 The systemmay provide lubrication monitoring, for example, where fluid viscosity increases and certain components might experience reduced functional life (e.g., in bearings). The systemmay issue an early warning that such phenomena might just begin to enact.

106 100 100 In using the laser sensor, the systemmay avoid more costly and larger optical systems which measure contaminants based on digital imaging processing using optical cameras where the focal distance renders the camera unusable. The systemmay be beneficially deployed in a confined space of the object. Further, conventional systems may be contaminated by the contaminant even with coatings because of the electrostatic characteristics.

100 104 The systemmay provide real time robust measurements, fast response with high sample rates, and measurements at close proximity to the object.

100 108 104 108 The systemincludes a sensor interface and image processing modulethat receives an image of the infrared laser light that is accumulated on the surface of the object. The sensor interface and image processing moduleprocesses the image.

100 The systemuses a combination of image characterization (statistical measurement of luminosity distribution over optical target) and image processing techniques correlated to provide for high accuracy in measurement.

110 112 The system includes a displayfor providing visual display to a user.

100 114 104 114 The systemmay include an image stitching modulethat provides a software function with a frozen visual representation of the object. The image stitching modulemay assemble the individual frames into a complete picture to provide a more detailed image analysis investigation.

106 106 100 In an embodiment, the laser sensortakes thousands of small (e.g., 2×2 mm) images (frames). The entire surface of interest (the one that collects the contaminant) is usually much larger. Those frames are acquired as the sensormoves above the surface of interest but not necessary in an order. In order to get a true image based on all the frames the systemsaves the frames temporarily in memory and, once finished, retrieves them in a sequence that permits assembling all of them in a square picture during the stitching process. A user may be able to then look at the final image and assess the parameters.

100 116 100 100 118 100 116 118 The systemincludes a test control modulethat includes the mechanical aspects of the system. The systemincludes a laser imaging systemthat includes the electrical aspects of the system. The functionality of the test control moduleis linked with the laser imaging system.

116 120 104 116 116 106 116 106 The test control moduleincludes a controllerfor controlling mechanical rotational actuation of the object. The test control moduleincludes controls providing accurate programmatic execution of testing schedule. The test control modulecontrols the sensorial equipment (e.g., the laser sensor) for positional synchronization. The test control modulepositions the laser sensorin a radial fashion at a desired aperture.

In variant embodiments, the system being tested may be any one or more of gearboxes, bearing surfaces, fuel tanks, structural monitoring (e.g., cracks/crack propagation), mining pump internals (e.g., rotor shaft eccentricity), mechanical interfaces, and faying surfaces.

106 106 12 0 100 The laser sensorincludes an exposure subsystem. The laser sensorworks with the exposure subsystem synchronously and at very fast rate. The exposure subsystem performs two exposures for each frame. For example, at,FPS (Frames Per Second) ambiental and infrared (IR) parasitic rejection is achieved. The first exposure is performed without activating the internal IR exposure sub-system. The second exposure is performed with activation of the internal IR exposure sub-system. Subsequently, the systemsubtracts from the second exposure the first one therefore eliminating parasitic ambiental “noise”.

118 106 118 108 The laser imaging systemacquires and interprets data coming from the laser sensor. The laser imaging systemincludes the hardware and the software part that controls the succession of actions that provide the resulting data. The sensor interface and image processing moduleprovides a user interface to receive commands. Commands may be entered through a standard serial interface (e.g., RS232C) or programmatically as content of an execution file stored on a memory (e.g., secure digital flash memory).

100 126 104 126 120 104 104 The systemincludes a position controllerfor controlling the position of the object. The position controllerincludes a driver for controlling the controllerthat may move the object(e.g., a stepper motor that rotates the object).

100 128 106 128 106 The systemincludes a laser controllerfor controlling the optical laser sensor. The laser controllerincludes a driver for controlling the controller to move the optical sensor.

126 128 200 104 126 200 128 106 The position controllerand the laser controllermay actuate and move the systemto explore the monitored surface of the object. The position controllermay be actuated in accordance with a test schedule. The test schedule provides movement so that the systemperforms as close as possible to real functionality. The laser controllermay be actuated by firmware that is synchronized in real time with the frames of the laser sensor.

100 122 122 122 The systemincludes a real time clock. The real time clockimplements a “time base” for the sequence of repeated frames acquisition. The real time clockis used for logging data by correlating measurements and program execution with the time these are performed so that the system can observe eventual events with the time they occurred.

100 100 The exposure subsystem may allow interface with a secure digital (SD) card (e.g., a small hard drive). The exposure subsystem may allow the systemto read and interpret the user program. The exposure subsystem may allow the systemto log the results and the time certain instructions were executed.

2 2 FIGS.A-D 1 FIG. 200 200 100 Referring to, there is a systemfor contaminant measurement, in accordance with an embodiment. The systemis an example system of the systemof, that tests for contamination in a rotary context, such as a rotary joint.

200 202 201 204 200 206 202 204 206 210 212 200 200 208 206 210 212 200 The systemincludes an interior ringthat rotates about axiswith respect to an exterior ring, which is fixed. The systemincludes a sealthat is positioned between the interior ringand the exterior ring. The sealseparates an external environmentfrom an internal cavityof the system. The systemdetermines the amount of contaminant(shown enlarged for illustration) that passes through the sealfrom the external environmentand into the internal cavityof the system.

200 214 216 200 218 208 220 220 216 201 220 208 222 The systemincludes a casethat houses a stepper motor. The systemincludes a collecting diskthat collects the contaminantonto a collecting tray. The collecting trayis conveyed by the stepper motorabout axis. The collecting trayconveys the contaminantto a scanning position.

200 224 106 222 220 208 224 220 1 FIG. The systemincludes a laser sensor(e.g., optical laser sensorof) at the scanning positionto scan the collecting trayfor contaminant. The laser sensoris sequentially positioned at successive tracks in order to perform a complete scan of the collecting tray.

2 FIG.C 200 226 220 228 As shown in, the systemmay include a home reference slotthat positions the collecting trayat a rotational home reference.

2 2 FIGS.C andD 200 230 224 220 200 232 224 200 224 As shown in, the systemincludes a translation actuation systemthat translates the laser sensorwith respect to the collecting tray. The systemincludes a translation slidefor sliding the laser sensor. The systemhas a translation home reference that positions the laser sensorat a translation home.

224 224 224 224 The laser sensormay be a high speed, low resolution imaging or a proximity sensing device. The laser sensormay be of various resolution types ranging from 9k pixels to over 32k pixels. The laser sensormay have high frame rates of 12K to 17K FPS. The laser sensormay have the ability to track speeds up to 60 inch/sec, while withstanding accelerations in excess of 50 G.

220 224 224 224 224 224 The collecting traymay be placed at about 2.4 mm away from the laser sensor. The distance from the laser sensoris taken into account when judging the resolution of the image. The laser sensormay have, for example, a physical size in the range of 1.8-2.2 sq. mm. The laser sensormay perform in the range of 4700-5200 DPI. The laser sensormay operate at wavelengths of 940-950 nm.

224 200 The laser sensormay be targeted towards determination of lunar dust (regolith) ingress through the dynamic sealed boundary of the system.

200 200 The systemperforms an optical laser scan. The optical laser scan may be a special operating-cycle that performs a complete rotation of the joint indexing sequential image sampling positions along track radius. The scan will result in a collection of sequential congruent images sampled across a circular sector placed underneath the joint rotating boundary. After completing the scan, the systeminfers a measurement that qualifies the degree of change in contaminant (e.g., regolith/simulant) accumulation since last scan was performed. Performing a scan cycle acquires a new data point in the timeline of the test schedule.

224 Several different scan cycles are defined and used for specific scope in the test schedule. There may not be a correlation between the scan response information and any quantification in terms of amount of contaminant accumulation. The limitation results both from the mathematical formulation of the detection procedure as well as the lack of calibration data that could be used to find appropriate dependency between the estimator and mass or volumetric accumulation of contaminant. Further deviation could result from IR response of the laser sensoralthough such errors may be small in comparison with the first two of them.

This limitation is due to the color variability of the contaminant particles. A small particle of darker color might have the same IR signature as a larger particle that is lighter.

200 The systemmay be used as a detector and a method to estimate the degree of change from the initial condition rather than a true measurement system. Proper correlation in terms of mass may be achieved by extracting the collecting trays and scaling the amount of accumulated material. However, a large number of particles retained on the collecting surface may alleviate this situation as variation of the reflection response rapidly diminishes when the number of particles becomes large and the mean of the sample approaches the mean of the population.

The scan returns a record set that each update a scan data file. The scan data file is a collection of data resulting from past performed scan operations.

200 200 200 226 200 234 200 226 The systemmay include a calibration phase. During the calibration phase the systemdetects several functional parameters that are geometrically and functionally dependent on the amount of contaminant deposition. The systemwill start a set of rotations with a fixed RPM and count the impulses of a gated crystal clock output to precisely determine the physical dimensions of the slots. The systemdetermines the position of a narrow slotthat acts as the “zero” index reference. The systemdetermines the value of the compensate factor to control motor rotation to the actually required user RPM. At the same time some functional parameters are adjusted as a function of the exact angular offset from the slotwhere frame sampling occurs during the scanning operation.

220 220 200 200 Scanning the substrate on the collecting trayis the principal method of evaluating the degree of contaminant accumulation past the joint barrier protection. Extracting the collection trayfor visual inspection may be an alternative option due to the risk that during the maneuvering process the layer of contaminant may change pattern therefore invalidating the baseline scan data. Scanning is an operation that depends on the geometric dimensions of the systemas well as on the kinematic movement. A scan operation may be performed if the calibration phase data has been altered. The calibration operation may be initialized as so often as required to ensure that the systemis aware of any changes that might have occurred since the last calibration.

200 The systemperforms the same calculations that would otherwise be performed for the scanning operation i.e. determining the perimeter of every detected grain of contaminant that penetrated the sealing boundary of the joint and summing the result.

Results may be assessed by using the scan command program instruction. Results may be assessed by visual inspection of each of the trays accumulation surface.

224 Assessing the amount of contaminant that penetrated the joint sealing boundary is done optically where the laser sensortakes sample frame snapshots at predefined locations on the collecting trays substrate defined by the angular position referenced by the corresponding slot and a radial track position. The scanning procedure begins at outermost radius and follows sequentially up to the last track. The number of tracks are customizable and are stored in a file. Each track has assigned a number of “frames” per tray (FPT) and this number is also defined inside the file.

Each of the frames undergoes an image processing procedure where eventually trapped simulant grains are identified and their perimeter is estimated. Actuation is briefly stopped allowing for image processing and persistent serialization on the SD card. A spectral analysis will translate that information into a number that is proportional to the length of the perimeter around the grain. That value is cumulated with similar values from all other frames and may be reported as a strip graph. Performing a scan operation may provide a new data point in the timeline of the testing process.

401 401 Scan results can also be visually analyzed. This utility is essentially a file converter that takes as input the scan data file and outputs a bitmap representation of that scan. A visual representation of this acquired image is presented in. The imageis the raw image. The processing performed includes rejecting the ambient parasitic IR as described above.

3 FIG. 4 FIG. 300 300 302 400 illustrates a methodof image processing, in accordance with an embodiment. The methodincludes receiving the IR sample at.illustrates a methodof image processing, in accordance with an embodiment.

304 402 At, the IR sample undergoes image processing () and edge detection. The presence of contaminant particles retained on the surface of each of the tray's substrate is identified and quantified using digital image processing techniques in a sequential succession.

304 404 404 406 406 404 includes dithering () the image. Ditheringis followed by neural network processing (). The neural network processing () may include two sequential differential operations. The first one is preparing the subsequent edge detection (another differential operator) by morphing the dark and light dots in a connected network. The ditheringoperates to avoid the possibility of very large values that can result from the differential operator application. The differential operator application includes a method to confine large numbers that could falsely result from transitions from bright to dark pixels.

In an embodiment, neural networks are defined as numbers of neurons and number of layers. Every neural network is in essence an approximator where the neural network tries to find a mathematical representation of the data at input and is doing that based on learning from examples that the user provides and that are deemed to be correct. A process called learning using labeled data and the neural network is called a convolutional neural network. The number of neurons influence the accuracy of approximation and the number of layers determine the ability to approximate non-linear dependency.

408 5 FIG. Subsequently, the method includes edge detectionand is followed by a normalization. The edge detection may be performed by a Sobel-Freidman operator. Differential operators may induce large variation in the values for transitions from bright to dark pixels, none of which may contain valuable information, as these result simply from the differentiation constants. The normalization groups all dark and all bright pixels in clusters allowing therefore for clear boundary identification as described with reference to.

304 300 At, in an embodiment, the methodincludes convoluting two orthogonal Sobel operators with every scanned frame and evaluating afterwards the size of the identified grain particle within the perimeter of the scan:

At every image pixel the two resulting gradient approximations are combined to result in the magnitude and the direction of the gradient.

306 At, a spectral histogram is performed.

308 At, an integrator is performed.

310 At, accumulation is performed.

4 FIG. 400 400 illustrates a methodof image processing, in accordance with an embodiment. The image processing methodmay be a Sobel edge detection sequence.

Since Sobel operators are differential in this embodiment, the image is initially dithered to prevent unbounded results in differential terms. A spectral analysis follower by an integrator block is translating the information of simulant grey signature of the perimeter into an optical estimate of accumulation.

Software control is achieved using a digital signal processor benefiting from a dedicated library that insulates the user from having to deal with low level access to the sensor using a dedicated HAL (Hardware Abstraction Layer). The library can be ported with little or no changes to many other applications of interest. The digital signal processor (DSP) may be using hardware multiplication barrel relieving the system from delays that may affect capability to acquire high rate frames.

401 106 402 401 304 A raw imageis supplied by an optical laser sensor (e.g., optical laser sensor). A digital signal processorperforms the core edge detection procedure by applying the Sobel differential operator to the raw imageas described with reference to.

401 If the analysis is simply performed directly on the acquired raw imagethe result would be an image that has a maximum contrast between the dark and light pixels because of the differential nature of operator. While that might be beneficial in certain applications, it may not be optimal for edge detection because certain softer edges would be missed.

400 404 403 403 405 The methodtrades some of the contrast for softer identification of differences. A Gauss dithering smoothing filterdithers the image to produce a dithered image. The dithered imageis directly fed to the segmentation procedure to create a resultwhere individual parts of the periphery envelope of contaminant grain are segmented into separate parts. For example, the signature that should identify the all-around periphery of the grain might be identified as the periphery of two separate grains of a smaller size. However, this might be appropriate for many other cases.

406 407 406 405 407 A morphological gradient estimatorgenerates an imagehaving morphological definition of the peripheric edges of contaminant grain, which is identified before differentiation. The morphological gradient estimatormay include a convolutional neural network trained to connect disparate contour lines into what would be the most probable signature of a larger contaminant grain periphery signatureand.

409 411 A Sobel-Friedman edge detection and normalization engine applies the Sobel operator to generate individual signatures that can be easily segregated as shown at image. Imageis a visual representation (full scale black and white of the final result).

5 5 5 FIGS.A,B, andC 500 502 504 illustrate user interfaces,,of a contaminant measurement system, in accordance with an embodiment.

502 502 504 4 5 FIGS.and The interfaceillustrates the result of applying the method ofin case of a contaminant particle approx. 0.1 mm in cross diagonal size. Interfacesandare explanatory on how the raw image transitioned into something that evaluates the contaminant particle perimeter/area.

The system may provide information in terms of visual percentage of change from a clean status and a pattern of deposition. Various techniques can be further used to translate this information in a quantifiable estimation of contaminant accumulation.

The system may include a monitoring tool. The monitoring tool is a screen driven utility that allows the user to qualify the substrate of the material that comes into contact with the contaminant—the collecting tray's substrate. The material has a constant reflecting response when exposed to the 940 nm IR Laser beam throughout the entire surface. The reflection response may be at a notable offset from the one of the contaminant grains and have a normal distribution around the mean value.

5 FIG.A 500 illustrates a displayof a control unit for the system. A contaminant particle is identified as returning a different reflection of the laser beam as compared with the one returned by the surface of the tray (so called reference surface or substrate surface). As a result, a large difference between these two response signatures may provide a good signal-to-noise ratio. The control unit includes a tool to facilitate placing a small amount of particles on a certain substrate and bringing the laser head into position to generate a spectral view of the response. The substrate response may be adjusted to be as far as possible from the one returned by the contaminant and one that has significantly lower amplitude than the one returned by contaminant. The tool serves as an aid in determining the best substrate surface for a given type of contaminant.

In some cases, a user may place a clean piece of an exploratory material underneath the sensor to analyze the amplitude response with and without contaminant.

5 FIG.A 500 504 In, the screendisplays an example image of a 2×2 mm wide instantaneous frame laying directly underneath the sensor. The screendisplays a spectral histogram of the gray repose of the same image. The histogram spreads from 0 (black) to 127—the maximum amount of “bright gray” that the sensor is capable of measuring.

The system described herein may monitor eventual changes in the level of accumulation visualizing the results as a heat map rather than as an image (e.g., where the magnitude of change seems to be of interest).

In order to precisely evaluate the optical reflection originating exclusively from the contaminant grains the user can place a clean piece of substrate sheet under the sensor and perform a spot baseline test. The spot baseline test may be extracted from the measurements therefore eliminating the contribution of the substrate. The visual scanning tool may include a screen driven application that indicates to the user the effectiveness of the edge detection procedure.

5 FIG.B 502 502 In, the screendisplays the image corresponding to actual location of the sensor. The system may perform the entire measurement procedure identifying and marking the boundary of the identified particles. The screenillustrates, drifted towards higher white spectrum, the boundary color remains proportional with the amplitude of the reflecting response.

While the above description provides examples of one or more apparatus, methods, or systems, it will be appreciated that other apparatus, methods, or systems may be within the scope of the claims as interpreted by one of skill in the art.